The TREC Spoken Document Retrieval Track: A Success Story
By John S. Garofolo, Cedric G. P. Auzanne, Ellen M. Voorhees. Text Retrieval Conference, 2000
463 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/57ee3a15088f2db36e07e3972e5dd9598b5284af
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Herman Kamper
- James R. Glass
- Karen Livescu
- Hung-yi Lee
- David F. Harwath
- Wei-Ning Hsu
- Yu-An Chung
- Lin-Shan Lee
Citations in the corpus
- On the Contributions of Visual and Textual Supervision in Low-resource Semantic Speech Retrieval (2019, unknown): “In semantic speech retrieval, the input is a textual query, a written word in our setting, and the task is to find utterances in a speech corpus that are semantically relevant to the query [14,15].”
- Application of information retrieval techniques to single writer documents (2005, background): “Experiments performed on speech recording transcriptions affected by WER between 10% and 40% show that, even in such a wide range, the retrieval performance changes only slightly (Garofolo et al., 1999).”
- Spoken Content Retrieval—Beyond Cascading Speech Recognition with Text Retrieval (2015, background): “Since obtaining his Ph.D. at MIT in Electrical Engineering and Computer Science, his research has focused on automatic speech recognition, unsupervised speech processing, and spoken language understanding.”
- Information Retrieval Evaluation (2011, background): “Two groups at NIST, the Speech group and the Retrieval group, collaborated to implement test collections for broadcast news for TRECs 6-8 [73].”
- Test Collection Based Evaluation of Information Retrieval Systems (2010, background): “• categorizing and/or retrieving streamed text, as addressed in the routing and filtering tracks [200]; • medical scholarly articles in the TREC-based genomics collection where matching to variants of gene names became a part of the search task [119]; • search across languages with English queries r”
- Semantic Speech Retrieval With a Visually Grounded Model of Untranscribed Speech (2017, background): “There has been some work on semantic speech retrieval [76]–[79]; the most common approach is to cascade ASR with text-based retrieval.”